Hello! I am currently a Postdoctoral Research Fellow at the School of Computing and Information Systems (SCIS), Singapore Management University (SMU), working with Prof. Guansong Pang and Prof. Debin Gao. Prior to joining SMU, I received my PhD degree from Beijing Institute of Technology (BIT), under the supervision of Prof. Zhendong Niu. My research interests focus on time series forecasting, anomaly detection, foundation models, foundation models for AIOps, and large language models for sequence data 
🔥 News
- 2025.08: 🎉🎉 One paper has been accepted by NeurIPS’25! Many thanks to my collaborators.
💼 Work Experience
- 2026.02 - Now, Postdoc, School of Computing and Information Systems, Singapore Management University, Singapore.
🎓 Educations
- 2020.09 - 2026.03, Ph.D., School of Medical Technology, Beijing Institute of Technologe, China.
- 2024.10 - 2025.10, Visiting Ph.D. Student, Machine Learning & Applications (MaLA) Lab, Singapore Management University, Singapore.
- 2017.09 - 2020.06, M.E., School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, China.
- 2013.09 - 2017.06, B.E., School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, China.
📝 Academic Service
- Reviewers
- IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS)
- IEEE Transactions on Multimedia (IEEE TMM)
- Information Fusion (IF)
- Knowledge-Based Systems (KBS)
- Machine Learning (ML)
- Neurocomputing
- PC Members
- AAAI 2023/2024/2025/2026
- IJCAI 2026
- KDD 2024/2026
- NeurIPS 2025/2026
- ICML 2026
- ICLR 2026
- ACM MM 2025/2026
- ACL ARR 2026
🎥 Tutorials
[KDD‘25 Tutorial]
Deep Learning in the Frequency Domain: Advances, Challenges, and Applications for Time Series Analysis,
Kun Yi, Qi Zhang, Wei Fan, Longbing Cao, Shoujin Wang, Hui He, Guodong Long, Liang Hu, Qingsong Wen, Hui Xiong
Tutorial at the 31st ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2025. [project] [website] [slides]
📖 Refereed Publications
† indicates co-first author; * indicates corresponding author. Full List
💡 2025
[NeurIPS 2025]
SEMPO: Lightweight Foundation Models for Time Series Forecasting,
Hui He, Kun Yi, Yuanchi Ma, Qi Zhang, Zhendong Niu, Guansong Pang
Advances in Neural Information Processing Systems, 2025. (CCF A) [pdf] [code]
[EMNLP 2025]
Boundary Matters: Leveraging Structured Text Plots for Long Text Outline Generation,
Yuanchi Ma, Jiamou Liu, Hui He, Libo Zhang, Haoyuan Li, Zhendong Niu
Findings of the Association for Computational Linguistics: EMNLP, Pages 49-63, 2025. (CCF B) [pdf] [code]
[KDD 2025]
A Survey on Deep Learning based Time Series Analysis with Frequency Transformation,
Kun Yi, Qi Zhang, Wei Fan, Longbing Cao, Shoujin Wang, Hui He, Guodong Long, Liang Hu, Qingsong Wen and Hui Xiong
Proceedings of the 31st SIGKDD Conference on Knowledge Discovery and Data Mining, Pages 6206-6215, 2025. (CCF A) [pdf]
[IEEE TCE]
Multi-KGS: Generating Social Network-based Meteorological Decision Reports Fusing with Multiple Knowledge,
Kaize Shi, Xueping Peng, Yifan Zhu, Hui He, Kun Yi, Zhendong Niu
IEEE Transactions on Consumer Electronics, Volume 71(3), Pages 8782-8789, 2025. (SCI Q2) [pdf] [code]
[IF]
Multimodal Nonparametric Clustering via Monte Carlo method and Fusion Embedding Generated by Variational Autoencoder,
Yuanchi Ma, Hui He, Gang Zhang, Zhendong Niu
Information Fusion, Pages 103612, 2025. (SCI Q1 CCF B) [pdf] [code]
[Neurocomputing]
DeepEDD: Nonparametric Deep Graph Clustering Through Effective Distance and Density,
Yuanchi Ma, Hui He, Zhongxiang Lei, Kaize Shi, Xueping Peng, Zhendong Niu
Neurocomputing, Pages 131359, 2025. (SCI Q2) [pdf] [code]
[IEEE TNNLS]
Robust Multivariate Time Series Forecasting against Intra- and Inter-Series Transitional Shift,
Hui He, Qi Zhang, Kun Yi, Xiaojun Xue, Shoujin Wang, Liang Hu, Longbing Cao
IEEE Transactions on Neural Networks and Learning Systems, Volume 36(12), Pages 20357-20370, 2025. (SCI Q1 CCF B) [pdf] [code]
[IEEE TNNLS]
Distributional Drift Adaptation with Temporal Conditional Variational Autoencoder for Multivariate Time Series Forecasting,
Hui He, Qi Zhang, Kun Yi, Kaize Shi, Zhendong Niu, Longbing Cao
IEEE Transactions on Neural Networks and Learning Systems, Volume 36(4), Pages 7287-7301, 2025. (SCI Q1 CCF B) [pdf]code]
💡 2024
[NeurIPS 2024]
FilterNet: Harnessing Frequency Filters for Time Series Forecasting,
Kun Yi, Jingru Fei, Qi Zhang, Hui He, Shufeng Hao, Defu Lian, Wei Fan
Advances in Neural Information Processing Systems, Volume 37, Pages 55115-55140, 2024. (CCF A) [pdf] [code]
[IEEE TCSS]
Deep Graph Clustering with Triple Fusion Mechanism for Community Detection,
Yuanchi Ma, Kaize Shi, Xueping Peng, Hui He, Peng Zhang, Jinyan Liu, Zhongxiang Lei, Zhendong Niu
IEEE Transactions on Computational Social System, Volume 12(4), Pages 1743-1758, 2024. (SCI Q3) [pdf] [code]
[ACM TOIS]
Deep Coupling Network for Multivariate Time Series Forecasting,
Kun Yi, Qi Zhang, Hui He, Kaize Shi, Liang Hu, Ning An, Zhendong Niu
ACM Transactions on Information System, Volume 42(5), Pages 1-28, 2024. (CCF A) [pdf] [code]
💡 2023
[NeurIPS 2023]
FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective,
Kun Yi, Qi Zhang, Wei Fan, Hui He, Liang Hu, Pengyang Wang, Ning An, Longbing Cao, Zhendong Niu
Advances in neural information processing systems, Volume 36, Pages 69638-69660, 2023. (CCF A) [pdf] [code]
[NeurIPS 2023]
Frequency-domain MLPs are More Effective Learners in Time Series Forecasting,
Kun Yi, Qi Zhang, Wei Fan, Shoujin Wang, Pengyang Wang, Hui He, Ning An, Defu Lian, Longbing Cao, Zhendong Niu
Advances in neural information processing systems, Volume 36, Pages 76656-76679, 2023. (CCF A) [pdf] [code]
[IEEE TKDE]
Learning Informative Representation for Fairness-aware Multivariate Time-series Forecasting: A Group-based Perspective,
Hui He, Qi Zhang, Shoujin Wang, Kun Yi, Zhendong Niu, Longbing Cao
IEEE Transactions on Knowledge and Data Engineering, Volume 36(6), Pages 2504-2516, 2023. (CCF A) [pdf] [code]
[Neurocomputing]
Cluster-aware attentive convolutional recurrent network for multivariate time-series forecasting,
Simeng Bai, Qi Zhang, Hui He, Liang Hu, Shoujin Wang, Zhendong Niu
Neurocomputing, Volume 558, Pages 126701, 2023. (SCI Q2) [pdf] [code]
💡 2022
[AAAI 2022]
CATN: Cross Attentive Tree-Aware Network for Multivariate Time Series Forecasting,
Hui He, Qi Zhang, Simeng Bai, Kun Yi, Zhendong Niu
Proceedings of the AAAI Conference on Artificial Intelligence, Volume 36(4), Pages 4030-4038, 2022. (CCF A) [pdf] [code]
📎 Friend Links
- Prof. Guansong Pang, Singapore Management University, Singapore
- Prof. Qi Zhang, Tongji University, China
- Dr. Kun Yi, State Information Center, China
- Dr. Hezhe Qiao, Singapore Management University, Singapore